Impact of crowding on the diversity of expanding populations

Author:

Schreck Carl F.123,Fusco Diana124ORCID,Karita Yuya5ORCID,Martis Stephen16,Kayser Jona127ORCID,Duvernoy Marie-Cécilia12,Hallatschek Oskar128ORCID

Affiliation:

1. Department of Physics, University of California, Berkeley, CA 94709

2. Department of Integrative Biology, University of California, Berkeley, CA 94709

3. Genomic Medicine Center, Children’s Mercy Hospital and Research Institute, Kansas, MO 64108

4. Department of Physics, University of Cambridge, Cambridge CB3 0HE, United Kingdom

5. Biophysics Graduate Group, University of California, Berkeley, CA 94709

6. Computational Oncology, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065

7. Max Planck Institute for the Science of Light, Max-Planck-Zentrum für Physik und Medizin, Erlangen 91058, Germany

8. Peter Debye Institute for Soft Matter Physics, Leipzig University, Leipzig 04103, Germany

Abstract

Crowding effects critically impact the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide, they push each other apart, remodeling the structure and extent of the population’s range. Recent work has shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes, which controls the fate of new variants as long as they are rare, remains unclear. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria–Delbrück fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically “pushed out” of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone-size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power law for low-frequency clones. Our model predicts that the distribution depends on a single parameter—the characteristic growth layer thickness—and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales.

Funder

HHS | NIH | National Institute of General Medical Sciences

NSF | MPS | Division of Physics

Simons Foundation

National Energy Research Scientific Computing Center

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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